Pythia: Scheduling of Concurrent Network packet Processing Applications on Heterogeneous Devices [EXTENDED VERSION]

TL;DR

This paper introduces an adaptive scheduling framework for heterogeneous network packet processing systems that optimally distributes workloads across diverse devices, improving performance and resource utilization in real-time scenarios.

Contribution

It presents a novel scheduling approach that supports any heterogeneous architecture, enabling concurrent application execution and interference mitigation in network processing.

Findings

Effective workload distribution across heterogeneous devices.

Robustness against runtime interference and fluctuations.

Improved response to traffic bursts and overloads.

Abstract

Modern commodity computing systems are composed by a number of different heterogeneous processing units, each of which has its own unique performance and energy characteristics. However, the majority of current network packet processing frameworks targets only a specific processing unit (either the CPU or accelerator), leaving the remaining computational resources under-utilized or even idle. In this paper, we propose an adaptive scheduling approach for network packet processing applications, that supports any heterogeneous and asymmetric architectures that can be found in a commodity high-end hardware setup. Our scheduler not only distributes the workloads to the appropriate devices in the system to achieve the desired performance results, but also enables the multiplexing of diverse network packet processing applications that execute concurrently, eliminating the interference effects introduced at runtime. The evaluation results show that our scheduler is able to tackle interferences in the shared hardware resources as well to respond quickly to dynamic fluctuations (e.g., application overloads, traffic bursts, infrastructural changes, etc.) that may occur at real time.